Estimating collision–coalescence rates from in situ observations of marine stratocumulus

• Published in: Quarterly journal of the Royal Meteorological Society 2017-10, Vol.143 (708), p.2755-2763
• Main Authors: Witte, Mikael K., Ayala, Orlando, Wang, Lian‐Ping, Bott, Andreas, Chuang, Patrick Y.
• Format: Article
• Language: English
• Subjects: Aircraft; Aircraft observations; Climate models; Cloud microphysics; Clouds; Coalescence; collision–coalescence; Constants; Drop size; Hydrodynamics; Kernels; Large-scale models; Length; Mathematical models; Numerical models; Physics; Precipitation; Rainfall; Scale models; Size distribution; Small-scale turbulence; Spatial distribution; Spatial variability; Spatial variations; Turbulence; Variability
• ISSN: 0035-9009; 1477-870X
• DOI: 10.1002/qj.3124

Precipitation forms in warm clouds via collision–coalescence. This process is difficult to observe directly in situ and its implementation in numerical models is uncertain. We use aircraft observations of the drop‐size distribution (DSD) near marine stratocumulus tops to estimate collision–coalescence rates. Marine stratocumulus is a useful system to study collisional growth because it is initiated near the cloud top and the clouds evolve slowly enough to obtain statistically useful data from aircraft. We compare rate constants estimated from observations with reference rate constants derived from a collision–coalescence box model, the result of which is termed the enhancement factor (EF). We evaluate two hydrodynamic collision–coalescence kernels, one quiescent and one including the effects of small‐scale turbulence. Due to sampling volume limitations, DSDs must be averaged over length‐scales much greater than those relevant to the underlying physics, such that we also examine the role of averaging length‐scale with respect to process representation. Averaging length‐scales of 1.5 and 30 km are used, corresponding roughly to the horizontal grid lengths of cloud‐resolving models and high‐resolution climate models, respectively. EF values range from 0.1 to 40, with the greatest EFs associated with small mode diameter cases and a generally decreasing trend with drop size. For any given drop size or averaging length‐scale, there is about an order of magnitude variability in EFs. These results suggest that spatial variability on length‐scales smaller than 1.5 km prevents accurate retrieval of rate constants from large‐scale average DSDs. Large‐scale models must therefore account for small‐scale variability to represent cloud microphysical processes accurately. The turbulent kernel reduces EFs for all drop sizes, but can only account for at most half of the calculated EFs in marine stratocumulus. Effective collision–coalescence rates are estimated from spatially averaged observations of the cloud drop‐size distribution. Enhancement factors, a comparison of observed rates with reference box model results generated using a quiescent or turbulent collision kernel, show that the observations and model results generally do not agree. This poor agreement is likely due to variability at smaller spatial scales than can be captured by the observations, which are limited by the sampling statistics of the cloud probe data analyzed.